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Evolvable hardware (EH) is a thriving area of research which uses the genetic algorithm (GA) to construct novel circuits without manual engineering.
Thus, the aim of the proposed optimisation procedure, which uses the genetic algorithm (GA), is to improve the spatial uniformity of temperature within the storage space.
The integrated PH/PH(n)/C/C discrete-event simulation (DES) model and optimization method that uses the genetic algorithm (GA) work together concurrently to obtain optimized (design) widths for different passenger flow and level of service (LOS) The numerical experiments are conducted to compare the proposed model with the existing design methods.
A PH/PH(n)/C/C DES model of walkway is developed in the SimEvents ® to estimate the necessary performance measures (blocking probabilities '(P_{c})' and mean area occupied per passenger 'ES') of walkway while the optimization method that uses the genetic algorithm (GA) is implemented in the MATLAB ® programming environment.
Similar(56)
The optimization methodology, using the genetic algorithm and the formulation of the problem are detailed.
This paper presents the optimal design of the magnetic microactuator using the genetic algorithm.
The most relevant molecular descriptors were selected using the genetic algorithm as a feature selection tool.
(3) Use the genetic algorithm to optimize the neural network response surface as the objective function.
The product unit cost is minimized while the exergy efficiency is maximized using the genetic algorithm.
The optimum structure of ANN has been designed using the genetic algorithm method.
Finally, the wide band absorbing material was designed using the genetic algorithm.
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CEO of Professional Science Editing for Scientists @ prosciediting.com